• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.97-111
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• 2020

In the 2015 revised curriculum, 'Integrated Science' was established to increase convergent thinking and designated as a common subject for all students to learn, regardless of career. In addition, the 2015 revised curriculum introduced 'competence' as a distinctive feature from the previous curriculum. In the 2015 revised curriculum, competencies are divided into core competencies of cross-curricular character and subject competencies based on academic knowledge and skills of the subject. The science curriculum contains five subject competencies: scientific thinking, scientific inquiry, scientific problem solving, scientific communication, scientific participation and life-long learning. However, the description of competencies in curriculum documents is insufficient, and experts' perceptions of competencies are not uniform. Therefore, this study examines the perceptions of science subjects in science high school teachers by deciding that comprehension of competencies should be preceded in order for competency-based education to be properly applied to school sites. First, we analyzed the relationship between achievement standards and subject competencies of integrated science through the operation of an expert working group with a high understanding of the integrated science achievement standards. Next, 31 high school science teachers examined the perception of the five subject competencies through a descriptive questionnaire. The semantic network analysis has been utilized to analyze the teachers' responses. The results of the analysis showed that the three curriculum competencies of scientific inquiry, scientific communication, scientific participation and life-long learning ability are similar to the definitions of teachers and curriculum documents, but in the case of scientific thinking and scientific problem solving, there are some gaps in perception and definition in curriculum documents. In addition, the results of the comprehensive analysis of teachers' perceptions on the five competencies show that the five curriculum competencies are more relevant than mutually exclusive or independent.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Journal of the Korean Wood Science and Technology
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• v.46 no.5
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• pp.597-609
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• 2018

Korea Forest Service has supplied 76 industrial wood pellet boilers from 2011 to 2015 through subsidy programs. Since carbon monoxide (CO) and nitrogen oxides ($NO_x$) generated during boiler combustion are substances that lead to death in the case of acute poisoning, it is very important to reduce emissions. Therefore, the CO and $NO_x$ emission values of 63 boilers excluding the hot air blower and some boilers initially supplied were analyzed. The emission factor was also calculated from the measured exhaust gas concentration (based on exhaust gas $O_2$ concentration of 12%). The average value of CO emitted from industrial wood pellet boilers was 49 ppm and it was confirmed that the CO concentration was decreasing as the years passed. The emission factor of CO was 0.73 g/kg. The average value of $NO_x$ emitted from industrial wood pellet boilers was 67 ppm and the emission factor of $NO_x$ was 1.63 g/kg. Unlike CO, there was no tendency to decrease according to the installation year. Both CO and $NO_x$ measurements met the limits of the Ministry of Environment. These $NO_x$ emission factors were compared with the $NO_x$ emission factors produced by certified low $NO_x$ burners. The $NO_x$ emission factor of industrial wood pellet boilers was about 1.9 times that of certified low $NO_x$ LNG combustors and about 0.92 times that of coal combustion.

• The Korean Society of Law and Medicine
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• v.17 no.2
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• pp.281-313
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• 2016

Our Constitution obliges the state to protect the health of the people, and the Medical Law, which embodied Constitution, sets out in detail the matters related to open the medical institution and one of them is to prohibit the operation of multiple medical institutions In the past, there was a provision stipulating the same purpose. But because the Supreme Court interpreted that several medical institutions could be opened if the medical treatment was not made at the additional medical instition which was opened in the another doctor,s license, multiple medical institutions could be opened and operated. However, some health care providers opened the several medical institutions to another doctor's license just by the excuse of the business management and then did illegal medical cares like the unfair luring of patients, overtreatment, and commition treatment for more profits. So, the health rights of the people came to be infringed on. Accordingly, lawmakers amended the Medical Law for medical personnel not to open and to operate more than one medical institution. As the amended medical law prohibited a medical personnel to open multiple medical institution, some medical personnels insisted that the amended medical law is unconstitutional under which they could not be able to open and operate medical institutions on based on free investment and bring out the benefits of network hospitals. But the regulation to prohibit multiple institutions does not apply only to a medical personnel. Many other experts like lawyer and pharmacist can open only one office under such a restriction. If the regulation goes out of force, the procedure that multiple medical institutions should be opened and operated in the capacity as a medical corporation or a non-profit corporation does not have to be followed. And we should keep in mind that the permission for medical personels to open multiple medical institutions could lead virtually to commercial hospital. If in the nation with a very low rate of public medical service, If only a few medical personnels with capital own many medical institutions and operate commercially them, this could cause a falling-off in quality of medical service, ultimately infringe on the health rights and the life right of the people.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.89-104
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• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Korean Society of Disaster and Security
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• v.17 no.1
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• pp.9-16
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• 2024

In Korea, as disasters become larger and more complex, there is a trend of shifting from a focus on response and recovery to a focus on prevention and preparedness. In order to prevent and prepare for disasters, each local government manages disaster management resources by stockpiling them. However, although disaster management resources are stored in individual warehouses, they are managed by department rather than by warehouse, resulting in insufficient management of disaster management resources due to the heavy workload of those in charge. In order to intensively manage these disaster management resources, an integrated disaster management resource management center is established and managed at the metropolitan/provincial level. In the case of Gangwon-do, the subject of this study, a warehouse is rented and operated as an integrated disaster management resource management center. When leasing an integrated management center, there is the inconvenience of having to move the location every 1 to 2 years, so it is deemed necessary to build a dedicated facility in an available site. To select a location candidate, network analysis was used to measure access to and use of facilities along interconnected routes of networks such as roads and railways. During network analysis, the Location-Allocation method, which was widely used in the past to determine the location of multiple facilities, was applied. As a result, Hoengseong-gun in Gangwon-do was identified as a suitable candidate site. In addition, if the integrated management center uses our country's logistics system to stockpile disaster management resources, local governments can mobilize disaster management resources in 3 days, and it is said that it takes 3 days to return to normal life after a disaster occurs. Each city's disaster management resource stockpile is 3 days' worth per week, and the integrated management center stores 3 times the maximum of the city's 4-day stockpile.

• Therapeutic Science for Rehabilitation
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• v.9 no.2
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• pp.99-117
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• 2020

Objective : The purpose of this study was to study the effects of occupation-based community rehabilitation on occupational performance skills and activities of daily living in stroke disabled persons living in the community, and to investigate the changes in occupation quality and satisfaction. Methods : In this single-subject ABA design study with follow-up evaluation, one severely disabled person diagnosed with stroke who lived in the community was recruited. The procedure consisted of a total of 25 sessions for 17 weeks. Intervention was according to occupation-based community rehabilitation, and the researcher visited the subject's home. Individualized intervention was applied according to the OTIPM. The intervention was composed of task assignment and feedback, home environment modification, information-related caregiver education, and community resource network. The evaluation of each session included the changes in the frequency of occupational performance skills, the quality of occupational performance in daily life, and the changes in occupational satisfaction, activities of daily living, quality of life, and maintenance of in the occupational performance skills during follow-up. The results were visually analyzed using a bar graph and a linear graph. Results : The results showed that the occupation-based community rehabilitation improved activities of daily living such as putting on socks, shoes slip-on, and upper body dressing garment within reach. Within the framework of the AMPS, it was confirmed that the quality of occupational performance was improved in all the subjects, and the degree of satisfaction also improved. Conclusion : This study showed that occupation-based rehabilitation can improve the occupational performance skills of stroke home disabled people positively affect the quality of occupational performance in daily life. Therefore, I think it is meaningful that useful for them.